A comparative machine learning approach for entropy-based damage detection using output-only correlation signal

Author:

Hamidian Pouria,Soofi Yasaman J.,Bitaraf MaryamORCID

Publisher

Springer Science and Business Media LLC

Subject

Safety, Risk, Reliability and Quality,Civil and Structural Engineering

Reference54 articles.

1. Farrar CR, Worden K (2012) Structural health monitoring: a machine learning perspective. Wiley, Hoboken

2. Rahmatabadi D, Tayyebi M, Najafizadeh N, Hashemi R, Rahmatabadi D, Tayyebi M et al (2018) Experimental investigation of formability of Al/Mg/Al strips fabricated via cold roll bonding process [Internet]. https://hal.archives-ouvertes.fr/hal-03086503

3. Najafizadeh N, Rajabi M, Hashemi R, Amini S (2019) Improved microstructure and mechanical properties of sheet metals in ultrasonic vibration enhanced biaxial stretch forming. J Theor Appl Vib Acoust 5(1):1–10

4. Najafizadeh N, Rajabi M, Hashemi R, Amini S (2021) A method and apparatus for determination of the ultrasonic-assisted forming limit diagram. Proc Inst Mech Eng Part C J Mech Eng Sci. https://doi.org/10.1177/09544062211011509

5. Amezquita-Sanchez JP, Adeli H (2016) Signal processing techniques for vibration-based health monitoring of smart structures. Arch Comput Methods Eng 23(1):1–15

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